Overview

Dataset statistics

Number of variables21
Number of observations2000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory328.2 KiB
Average record size in memory168.1 B

Variable types

NUM14
BOOL6
CAT1

Warnings

price_range is highly correlated with ramHigh correlation
ram is highly correlated with price_rangeHigh correlation
price_range is uniformly distributed Uniform
fc has 474 (23.7%) zeros Zeros
pc has 101 (5.1%) zeros Zeros
sc_w has 180 (9.0%) zeros Zeros

Reproduction

Analysis started2020-12-11 08:47:10.568574
Analysis finished2020-12-11 08:47:36.278944
Duration25.71 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

battery_power
Real number (ℝ≥0)

Distinct1094
Distinct (%)54.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1238.5185
Minimum501
Maximum1998
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-12-11T17:47:36.367975image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum501
5-th percentile570.95
Q1851.75
median1226
Q31615.25
95-th percentile1930.15
Maximum1998
Range1497
Interquartile range (IQR)763.5

Descriptive statistics

Standard deviation439.4182061
Coefficient of variation (CV)0.3547934133
Kurtosis-1.224143883
Mean1238.5185
Median Absolute Deviation (MAD)382
Skewness0.03189847179
Sum2477037
Variance193088.3598
MonotocityNot monotonic
2020-12-11T17:47:36.484971image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
158960.3%
 
61860.3%
 
187260.3%
 
137950.2%
 
131050.2%
 
106350.2%
 
83250.2%
 
141450.2%
 
141350.2%
 
180750.2%
 
Other values (1084)194797.4%
 
ValueCountFrequency (%) 
50120.1%
 
50220.1%
 
50330.1%
 
50450.2%
 
50610.1%
 
ValueCountFrequency (%) 
199810.1%
 
199710.1%
 
199620.1%
 
199520.1%
 
199430.1%
 

blue
Boolean

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
0
1010 
1
990 
ValueCountFrequency (%) 
0101050.5%
 
199049.5%
 
2020-12-11T17:47:36.566972image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

clock_speed
Real number (ℝ≥0)

Distinct26
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.52225
Minimum0.5
Maximum3
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-12-11T17:47:36.626975image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile0.5
Q10.7
median1.5
Q32.2
95-th percentile2.8
Maximum3
Range2.5
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation0.8160042089
Coefficient of variation (CV)0.5360513772
Kurtosis-1.323417222
Mean1.52225
Median Absolute Deviation (MAD)0.8
Skewness0.1780841203
Sum3044.5
Variance0.6658628689
MonotocityNot monotonic
2020-12-11T17:47:36.730971image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%) 
0.541320.6%
 
2.8854.2%
 
2.3783.9%
 
1.6763.8%
 
2.1763.8%
 
2.5743.7%
 
0.6743.7%
 
1.4703.5%
 
1.3683.4%
 
2673.4%
 
Other values (16)91946.0%
 
ValueCountFrequency (%) 
0.541320.6%
 
0.6743.7%
 
0.7643.2%
 
0.8582.9%
 
0.9582.9%
 
ValueCountFrequency (%) 
3281.4%
 
2.9623.1%
 
2.8854.2%
 
2.7552.8%
 
2.6552.8%
 

dual_sim
Boolean

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
1
1019 
0
981 
ValueCountFrequency (%) 
1101950.9%
 
098149.0%
 
2020-12-11T17:47:36.801978image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

fc
Real number (ℝ≥0)

ZEROS

Distinct20
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3095
Minimum0
Maximum19
Zeros474
Zeros (%)23.7%
Memory size15.6 KiB
2020-12-11T17:47:36.859979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q37
95-th percentile13
Maximum19
Range19
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.341443748
Coefficient of variation (CV)1.007412402
Kurtosis0.2770763246
Mean4.3095
Median Absolute Deviation (MAD)3
Skewness1.019811411
Sum8619
Variance18.84813382
MonotocityNot monotonic
2020-12-11T17:47:36.946971image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%) 
047423.7%
 
124512.2%
 
21899.4%
 
31708.5%
 
51397.0%
 
41336.7%
 
61125.6%
 
71005.0%
 
9783.9%
 
8773.9%
 
Other values (10)28314.1%
 
ValueCountFrequency (%) 
047423.7%
 
124512.2%
 
21899.4%
 
31708.5%
 
41336.7%
 
ValueCountFrequency (%) 
1910.1%
 
18110.5%
 
1760.3%
 
16241.2%
 
15231.1%
 

four_g
Boolean

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
1
1043 
0
957 
ValueCountFrequency (%) 
1104352.1%
 
095747.9%
 
2020-12-11T17:47:37.013972image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

int_memory
Real number (ℝ≥0)

Distinct63
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.0465
Minimum2
Maximum64
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-12-11T17:47:37.087972image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q116
median32
Q348
95-th percentile61
Maximum64
Range62
Interquartile range (IQR)32

Descriptive statistics

Standard deviation18.14571496
Coefficient of variation (CV)0.5662307882
Kurtosis-1.21607403
Mean32.0465
Median Absolute Deviation (MAD)16
Skewness0.05788932785
Sum64093
Variance329.2669712
MonotocityNot monotonic
2020-12-11T17:47:37.206971image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
27472.4%
 
14452.2%
 
16452.2%
 
2422.1%
 
57422.1%
 
7402.0%
 
42402.0%
 
44391.9%
 
30391.9%
 
6371.8%
 
Other values (53)158479.2%
 
ValueCountFrequency (%) 
2422.1%
 
3251.2%
 
4201.0%
 
5361.8%
 
6371.8%
 
ValueCountFrequency (%) 
64311.6%
 
63301.5%
 
62211.1%
 
61271.4%
 
60271.4%
 

m_dep
Real number (ℝ≥0)

Distinct10
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.50175
Minimum0.1
Maximum1
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-12-11T17:47:37.311971image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.1
Q10.2
median0.5
Q30.8
95-th percentile1
Maximum1
Range0.9
Interquartile range (IQR)0.6

Descriptive statistics

Standard deviation0.2884155496
Coefficient of variation (CV)0.5748192319
Kurtosis-1.274348884
Mean0.50175
Median Absolute Deviation (MAD)0.3
Skewness0.08908200979
Sum1003.5
Variance0.08318352926
MonotocityNot monotonic
2020-12-11T17:47:37.390972image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0.132016.0%
 
0.221310.7%
 
0.820810.4%
 
0.520510.2%
 
0.720010.0%
 
0.319910.0%
 
0.91959.8%
 
0.61869.3%
 
0.41688.4%
 
11065.3%
 
ValueCountFrequency (%) 
0.132016.0%
 
0.221310.7%
 
0.319910.0%
 
0.41688.4%
 
0.520510.2%
 
ValueCountFrequency (%) 
11065.3%
 
0.91959.8%
 
0.820810.4%
 
0.720010.0%
 
0.61869.3%
 

mobile_wt
Real number (ℝ≥0)

Distinct121
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean140.249
Minimum80
Maximum200
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-12-11T17:47:37.490981image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum80
5-th percentile86
Q1109
median141
Q3170
95-th percentile196
Maximum200
Range120
Interquartile range (IQR)61

Descriptive statistics

Standard deviation35.3996549
Coefficient of variation (CV)0.2524057562
Kurtosis-1.210376474
Mean140.249
Median Absolute Deviation (MAD)31
Skewness0.006558157429
Sum280498
Variance1253.135567
MonotocityNot monotonic
2020-12-11T17:47:37.615971image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
182281.4%
 
185271.4%
 
101271.4%
 
146261.3%
 
199261.3%
 
88251.2%
 
105251.2%
 
198251.2%
 
89241.2%
 
145231.1%
 
Other values (111)174487.2%
 
ValueCountFrequency (%) 
80211.1%
 
81130.7%
 
82150.8%
 
83190.9%
 
84170.9%
 
ValueCountFrequency (%) 
200190.9%
 
199261.3%
 
198251.2%
 
197190.9%
 
196201.0%
 

n_cores
Real number (ℝ≥0)

Distinct8
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5205
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-12-11T17:47:37.717973image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median4
Q37
95-th percentile8
Maximum8
Range7
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.287836718
Coefficient of variation (CV)0.5061025811
Kurtosis-1.229749767
Mean4.5205
Median Absolute Deviation (MAD)2
Skewness0.003627508314
Sum9041
Variance5.234196848
MonotocityNot monotonic
2020-12-11T17:47:37.794947image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
427413.7%
 
725913.0%
 
825612.8%
 
224712.3%
 
524612.3%
 
324612.3%
 
124212.1%
 
623011.5%
 
ValueCountFrequency (%) 
124212.1%
 
224712.3%
 
324612.3%
 
427413.7%
 
524612.3%
 
ValueCountFrequency (%) 
825612.8%
 
725913.0%
 
623011.5%
 
524612.3%
 
427413.7%
 

pc
Real number (ℝ≥0)

ZEROS

Distinct21
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.9165
Minimum0
Maximum20
Zeros101
Zeros (%)5.1%
Memory size15.6 KiB
2020-12-11T17:47:37.884947image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median10
Q315
95-th percentile20
Maximum20
Range20
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.064314941
Coefficient of variation (CV)0.6115378351
Kurtosis-1.171498795
Mean9.9165
Median Absolute Deviation (MAD)5
Skewness0.01730615047
Sum19833
Variance36.77591571
MonotocityNot monotonic
2020-12-11T17:47:38.204947image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%) 
101226.1%
 
71195.9%
 
91125.6%
 
201105.5%
 
141045.2%
 
11045.2%
 
01015.1%
 
2995.0%
 
17995.0%
 
6954.8%
 
Other values (11)93546.8%
 
ValueCountFrequency (%) 
01015.1%
 
11045.2%
 
2995.0%
 
3934.7%
 
4954.8%
 
ValueCountFrequency (%) 
201105.5%
 
19834.2%
 
18824.1%
 
17995.0%
 
16884.4%
 

px_height
Real number (ℝ≥0)

Distinct1137
Distinct (%)56.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean645.108
Minimum0
Maximum1960
Zeros2
Zeros (%)0.1%
Memory size15.6 KiB
2020-12-11T17:47:38.318946image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile70.95
Q1282.75
median564
Q3947.25
95-th percentile1485.05
Maximum1960
Range1960
Interquartile range (IQR)664.5

Descriptive statistics

Standard deviation443.7808108
Coefficient of variation (CV)0.6879170787
Kurtosis-0.3158654936
Mean645.108
Median Absolute Deviation (MAD)318
Skewness0.6662712561
Sum1290216
Variance196941.408
MonotocityNot monotonic
2020-12-11T17:47:38.434946image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
34770.4%
 
17960.3%
 
37160.3%
 
27560.3%
 
52650.2%
 
32750.2%
 
67450.2%
 
66750.2%
 
35650.2%
 
5650.2%
 
Other values (1127)194597.2%
 
ValueCountFrequency (%) 
020.1%
 
110.1%
 
210.1%
 
320.1%
 
430.1%
 
ValueCountFrequency (%) 
196010.1%
 
194910.1%
 
192010.1%
 
191410.1%
 
190110.1%
 

px_width
Real number (ℝ≥0)

Distinct1109
Distinct (%)55.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1251.5155
Minimum500
Maximum1998
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-12-11T17:47:38.554946image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile579.85
Q1874.75
median1247
Q31633
95-th percentile1929.05
Maximum1998
Range1498
Interquartile range (IQR)758.25

Descriptive statistics

Standard deviation432.1994469
Coefficient of variation (CV)0.3453408663
Kurtosis-1.186005229
Mean1251.5155
Median Absolute Deviation (MAD)376
Skewness0.01478747377
Sum2503031
Variance186796.3619
MonotocityNot monotonic
2020-12-11T17:47:38.670946image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
87470.4%
 
124770.4%
 
138360.3%
 
146960.3%
 
146360.3%
 
142950.2%
 
172650.2%
 
192350.2%
 
123450.2%
 
126350.2%
 
Other values (1099)194397.2%
 
ValueCountFrequency (%) 
50020.1%
 
50120.1%
 
50310.1%
 
50610.1%
 
50740.2%
 
ValueCountFrequency (%) 
199810.1%
 
199710.1%
 
199610.1%
 
199530.1%
 
199420.1%
 

ram
Real number (ℝ≥0)

HIGH CORRELATION

Distinct1562
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2124.213
Minimum256
Maximum3998
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-12-11T17:47:38.792946image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum256
5-th percentile445
Q11207.5
median2146.5
Q33064.5
95-th percentile3826.35
Maximum3998
Range3742
Interquartile range (IQR)1857

Descriptive statistics

Standard deviation1084.732044
Coefficient of variation (CV)0.5106512594
Kurtosis-1.19191307
Mean2124.213
Median Absolute Deviation (MAD)932.5
Skewness0.006628035399
Sum4248426
Variance1176643.606
MonotocityNot monotonic
2020-12-11T17:47:38.906945image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
261040.2%
 
222740.2%
 
314240.2%
 
146440.2%
 
122940.2%
 
31530.1%
 
195830.1%
 
127730.1%
 
172430.1%
 
370330.1%
 
Other values (1552)196598.2%
 
ValueCountFrequency (%) 
25610.1%
 
25820.1%
 
25910.1%
 
26210.1%
 
26310.1%
 
ValueCountFrequency (%) 
399810.1%
 
399610.1%
 
399310.1%
 
399120.1%
 
399010.1%
 

sc_h
Real number (ℝ≥0)

Distinct15
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.3065
Minimum5
Maximum19
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-12-11T17:47:39.006946image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile6
Q19
median12
Q316
95-th percentile19
Maximum19
Range14
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.213245004
Coefficient of variation (CV)0.3423593227
Kurtosis-1.190791247
Mean12.3065
Median Absolute Deviation (MAD)4
Skewness-0.09888424098
Sum24613
Variance17.75143347
MonotocityNot monotonic
2020-12-11T17:47:39.088946image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%) 
171939.7%
 
121577.8%
 
71517.5%
 
161437.1%
 
141437.1%
 
151356.8%
 
131316.6%
 
111266.3%
 
101256.2%
 
191246.2%
 
Other values (5)57228.6%
 
ValueCountFrequency (%) 
5974.9%
 
61145.7%
 
71517.5%
 
81175.9%
 
91246.2%
 
ValueCountFrequency (%) 
191246.2%
 
181206.0%
 
171939.7%
 
161437.1%
 
151356.8%
 

sc_w
Real number (ℝ≥0)

ZEROS

Distinct19
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.767
Minimum0
Maximum18
Zeros180
Zeros (%)9.0%
Memory size15.6 KiB
2020-12-11T17:47:39.179945image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q39
95-th percentile14
Maximum18
Range18
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.356397606
Coefficient of variation (CV)0.7554010067
Kurtosis-0.3895227894
Mean5.767
Median Absolute Deviation (MAD)3
Skewness0.6337870734
Sum11534
Variance18.9782001
MonotocityNot monotonic
2020-12-11T17:47:39.271957image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%) 
121010.5%
 
319910.0%
 
41829.1%
 
01809.0%
 
51618.1%
 
21567.8%
 
71326.6%
 
61306.5%
 
81256.2%
 
101075.3%
 
Other values (9)41820.9%
 
ValueCountFrequency (%) 
01809.0%
 
121010.5%
 
21567.8%
 
319910.0%
 
41829.1%
 
ValueCountFrequency (%) 
1880.4%
 
17190.9%
 
16291.5%
 
15311.6%
 
14331.7%
 

talk_time
Real number (ℝ≥0)

Distinct19
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.011
Minimum2
Maximum20
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-12-11T17:47:39.369957image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q16
median11
Q316
95-th percentile20
Maximum20
Range18
Interquartile range (IQR)10

Descriptive statistics

Standard deviation5.463955198
Coefficient of variation (CV)0.4962269728
Kurtosis-1.218590963
Mean11.011
Median Absolute Deviation (MAD)5
Skewness0.009511762222
Sum22022
Variance29.8548064
MonotocityNot monotonic
2020-12-11T17:47:39.457957image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%) 
71246.2%
 
41236.2%
 
161165.8%
 
151155.8%
 
191135.7%
 
61115.5%
 
101055.2%
 
81045.2%
 
111035.1%
 
201025.1%
 
Other values (9)88444.2%
 
ValueCountFrequency (%) 
2995.0%
 
3944.7%
 
41236.2%
 
5934.7%
 
61115.5%
 
ValueCountFrequency (%) 
201025.1%
 
191135.7%
 
181005.0%
 
17984.9%
 
161165.8%
 

three_g
Boolean

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
1
1523 
0
477 
ValueCountFrequency (%) 
1152376.1%
 
047723.8%
 
2020-12-11T17:47:39.528959image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
1
1006 
0
994 
ValueCountFrequency (%) 
1100650.3%
 
099449.7%
 
2020-12-11T17:47:39.562959image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

wifi
Boolean

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
1
1014 
0
986 
ValueCountFrequency (%) 
1101450.7%
 
098649.3%
 
2020-12-11T17:47:39.595960image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

price_range
Categorical

HIGH CORRELATION
UNIFORM

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
3
500 
2
500 
1
500 
0
500 
ValueCountFrequency (%) 
350025.0%
 
250025.0%
 
150025.0%
 
050025.0%
 
2020-12-11T17:47:39.660957image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-11T17:47:39.722958image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:39.794958image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

Interactions

2020-12-11T17:47:14.114194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:14.234230image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:14.341199image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:14.452194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:14.558194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:14.664194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:14.846230image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:14.958224image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:15.069198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:15.185203image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:15.305194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:15.422197image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:15.531198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:15.642199image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:15.749198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:15.849198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:15.944198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:16.043199image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:16.139198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:16.232197image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:16.329198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:16.427198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:16.527197image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:16.629198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:16.732194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:16.832193image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:16.927194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:17.025194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:17.125194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:17.233195image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:17.341222image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:17.448217image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:17.553225image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:17.651222image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:17.755224image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:17.950232image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:18.066200image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:18.174197image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:18.279198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:18.384197image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:18.485198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:18.588197image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:18.694198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:18.796198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:18.893198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:19.060199image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:19.200195image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:19.301195image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:19.407195image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:19.524195image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:19.628195image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:19.731194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:19.831194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:19.933194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:20.030196image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:20.131196image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:20.232196image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:20.327196image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:20.419222image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:20.515259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:20.611259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:20.700259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:20.794259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:20.894259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:20.994233image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:21.092233image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:21.187233image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:21.282233image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:21.373235image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:21.470233image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:21.568233image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:21.783235image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:21.887233image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:21.988234image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:22.086231image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:22.180231image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:22.279231image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:22.379232image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:22.484231image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:22.587231image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:22.691261image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:22.794261image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:22.893260image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:22.996258image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:23.101259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:23.213266image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:23.314259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:23.418263image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:23.519260image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:23.616261image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:23.719259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:23.822259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:23.928260image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:24.035262image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:24.140259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:24.246260image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:24.346259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:24.449262image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:24.554261image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:24.663260image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:24.768259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:24.876262image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:24.982261image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:25.083259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:25.190261image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:25.303260image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:25.415269image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:25.528261image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:25.637252image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:25.749259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:25.854256image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:25.966259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:26.077259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:26.327231image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:26.438231image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:26.545232image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:26.649230image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:26.748231image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:26.859232image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:26.973252image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:27.089894image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:27.210868image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:27.324863image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:27.444864image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:27.559864image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:27.675866image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:27.793866image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:27.903865image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:28.006891image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:28.113893image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:28.251869image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:28.406867image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:28.523866image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:28.631898image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:28.739891image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:28.847891image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:28.958898image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:29.113868image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:29.261865image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:29.368863image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:29.475502image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:29.577617image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:29.679738image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:29.781943image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:29.884074image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:29.976038image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:30.078200image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:30.185997image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:30.293996image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:30.401996image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:30.508997image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:30.620971image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:30.720971image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:30.824972image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:30.928972image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:31.043014image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:31.154968image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:31.263580image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:31.382143image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:31.491391image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:31.608690image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:31.707254image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:31.809610image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:31.911090image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:32.018681image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:32.288765image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:32.405768image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:32.512763image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:32.614764image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:32.725769image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:32.834770image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:32.943763image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:33.046763image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:33.146763image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:33.250763image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:33.354763image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:33.462763image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:33.572762image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:33.682767image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:33.800991image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:33.928948image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:34.034972image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:34.142948image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:34.267952image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:34.373972image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:34.487972image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:34.591971image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:34.691972image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:34.796973image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:34.902972image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:35.010972image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:35.121972image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:35.231972image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:35.338972image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:35.446959image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:35.564959image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2020-12-11T17:47:39.899957image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-12-11T17:47:40.112959image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-12-11T17:47:40.325957image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-12-11T17:47:40.537957image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-12-11T17:47:35.813971image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-11T17:47:36.153944image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

battery_powerblueclock_speeddual_simfcfour_gint_memorym_depmobile_wtn_corespcpx_heightpx_widthramsc_hsc_wtalk_timethree_gtouch_screenwifiprice_range
084202.201070.61882220756254997190011
1102110.5101530.7136369051988263117371102
256310.5121410.91455612631716260311291102
361512.5000100.813169121617862769168111002
4182111.20131440.614121412081212141182151101
5185900.5130220.716417100416541067171101001
6182101.7041100.813981038110183220138181013
7195400.5100240.818740512114970016351110
8144510.5000530.71747143868361099171201000
950910.612190.193515113712245131910121000

Last rows

battery_powerblueclock_speeddual_simfcfour_gint_memorym_depmobile_wtn_corespcpx_heightpx_widthramsc_hsc_wtalk_timethree_gtouch_screenwifiprice_range
1990161712.4081360.8851974314262965371000
1991188202.00111440.811381947433579198201103
199267412.9110210.219834576180911806341110
1993146710.5000180.61225088810993962151151113
199485802.2010500.1841252814163978171631103
199579410.510120.810661412221890668134191100
1996196512.6100390.218743915196520321110161112
1997191100.9111360.710883868163230579151103
1998151200.9041460.1145553366708691810191110
199951012.0151450.9168616483754391919421113